基于改进蝴蝶搜索算法的DGPS整周模糊度快速解算

Fast resolution of DGPS integer ambiguity based on improved butterfly optimization algorithm

为了快速准确地解算差分全球定位系统(DGPS)整周模糊度,提出了一种改进蝴蝶搜索算法(IBOA)求解整周模糊度。首先在蝴蝶优化算法(BOA)的香味系数中加入一个自适应权重,弥补BOA算法觅食行为中较弱的搜索能力;其次使用动态切换概率权衡BOA算法中全局搜索与局部搜索的比例;最后在全局搜索和局部搜索阶段引入新的迭代位置更新策略,提升了算法全局搜索能力和跳出局部最优能力。与最小二乘模糊度降相关平差算法(LAMBDA)算法进行1000个历元数据的解算对比实验,结果表明所提算法的平均搜索成功率比LAMBDA算法提高了5.07%。

The proposed solution to effectively and accurately address the integer ambiguity of differential global positioning system(DGPS)is an improved butterfly optimization algorithm(IBOA).Firstly,an adaptive weight is introduced to enhance the pheromone coefficient of the butterfly optimization algorithm(BOA),compensating for its limited searching capability in foraging behavior.Secondly,a dynamic switching probability is employed to balance the proportions of global search and local search in BOA algorithm.Finally,a novel iterative location update strategy is incorporated into both global search and local search phases,thereby enhancing both global exploration ability and local optimization ability of the algorithm.Compared with the LAMBDA algorithm for solving 1000 epoch data,the results show that the average search success rate of the proposed algorithm is 5.07%higher than that of the LAMBDA algorithm.